Provides ranking service and interface embedded into a curation platform. NeXtA5 aims to supply an annotation workflow that will leverage automated methods for text analysis to speed up curation and furnish a better ranking of MEDLINE articles. Searches can be made by using two methods: by performing Boolean queries directly using PubMed via the e-Utils and by using a search engine based on a vector-space model that locally indexes the content of MEDLINE.
BiTeM Group, University of Applied Sciences, Western Switzerland-HEG Genève, Information Science Department, Suisse; SIB Text Mining, Swiss Institute of Bioinformatics, Suisse; Calipho Group, Swiss Institute of Bioinformatics, Suisse
neXtA5 funding source(s)
Supported by the Swiss National Fund for Scientific Research, SNF Grant: [neXtPresso project, SNF #153437]; [Elixir-Excelerate, Grant # 676559] and [MD-Paedigree, Grant # 600932], which respectively support the development of the BioMed database and the services to automatically annotate the content of BioMed (MeSH indexing).